What Students Gain When Teachers — Not AI — Grade Students’ Work

Beyond the Algorithm: Why Human Eyes Still Reign Supreme in Student Assessment

In a rapidly evolving educational landscape, the allure of artificial intelligence for grading student work is undeniable. Yet, a veteran educator's transformative year with seventh graders offers a potent reminder: the nuanced, empathetic judgment of a human teacher remains an irreplaceable cornerstone of genuine student learning.

The Foundation of Flight: Building Mastery from the Ground Up

Masheika Allgood, a lawyer-turned-ethicist with a deep passion for teaching, recounts a pivotal year shaping her pedagogical approach. Her mission was not merely to navigate the academic year but to ignite a love for learning in every seventh-grade English language arts student she encountered.

Having already amassed significant academic credentials, Allgood entered the public middle school classroom with a clear objective: to ensure each student possessed a robust academic foundation. This, she believed, was the essential preparation for future success, allowing every student to "fly" when the time was right.

Diagnostic Deep Dive: Uncovering True Understanding

The journey began with meticulous diagnostic assessments, a critical inventory of each student's existing knowledge. Allgood understood that bright students could sometimes mask skill gaps, and assumptions about lower-achieving students often proved inaccurate.

She carefully selected assessment areas aligned with the year's learning objectives and fundamental skills. For instance, she recognized that analyzing literature requires a solid grasp of comparison and contrast, skills that were directly evaluated.

Following the initial assessments, Allgood provided personalized feedback and coaching, guiding students to integrate these insights into their learning. This foundational work was paramount to her strategy.

The Shifting Landscape of Assessment

By 2022, a staggering 94 percent of educators reported utilizing learning management systems (LMS). These platforms, including widely adopted tools, are instrumental in managing course content, collecting assignments, and automating grading and assessment processes.

Allgood then embarked on a detailed analysis of the diagnostic data, comparing performance across her classes. She developed a visual mapping system to track each student's progress, using this data to inform her lesson planning.

While core fundamentals were taught uniformly, her instruction was dynamically adjusted. She strategically emphasized specific areas based on the collective strengths and weaknesses identified in her student data.

Reassessment and Renaissance: Creative Pathways to Mastery

After approximately four to five weeks, students were reassessed through a variety of creative means. This included composing songs to explain grammatical concepts, developing crossword puzzles on key reading points, and identifying audio foreshadowing in film clips.

Alongside these engaging activities, traditional quizzes and assignments were administered. By the time the Christmas break arrived, Allgood's students had demonstrably mastered the seventh-grade fundamentals.

This mastery unlocked the second half of the year, a period where deeper learning and exploration could truly flourish. The students were ready to "fly."

Soaring to New Heights: Literature, Debate, and Unexpected Triumphs

With a solid foundation in place, the class delved into a full-length fiction novel, an experience many students had never before undertaken. The engagement soared because the learning was tailored to resonate with their interests and experiences.

Activities included creating timelines of significant plot events, writing letters from the perspectives of characters offering future advice, and participating in spirited debates. One particularly memorable debate centered on the legality of "mailbox baseball," prompting a student to research and cite federal code regarding mailbox tampering.

This moment, Allgood shared, was one of the proudest of her teaching career, illustrating the profound impact of fostering critical thinking and research skills.

Inclusivity in Achievement: Bridging Diverse Learning Needs

The success was not confined to honors classes. Students with learning and behavioral disabilities, speech and hearing impairments, and those who had frequently faced disciplinary issues were all part of this academic ascent.

Allgood's intentional approach to building fundamental skills in the first half of the year empowered these students to tackle higher-order concepts. They developed the necessary grammar, vocabulary, and critical thinking abilities to succeed.

The carefully designed lesson plans and reassessments, informed by diagnostic data, were instrumental in closing learning gaps and ensuring every student could participate and excel.

The Observer's Astonishment: A Testament to Effective Teaching

An observing teacher at the end of the school year noted an astonishing similarity in performance between Allgood's honors and other classes, observing that all students were working at an advanced level.

One student, notorious for frequent visits to the principal's office, not only passed the class but, along with every other student, also succeeded on the state exam.

This outcome underscores the critical importance of the research series, highlighting Allgood's passion for diagnostics and assessments, born from witnessing their transformative power. She firmly believes that every student can achieve success when provided with the right foundational learning.

The Central Question: How Do We Truly Know Students Are Learning?

Allgood's teaching philosophy is anchored by a fundamental question: "How do we know that students are learning?" This inquiry also fueled her involvement in the current research project.

In an era dominated by ubiquitous student learning platforms and educational technology, the methods of diagnostics and assessment are evolving. The crucial questions remain: How are these processes conducted? How do they inform lesson plans and course objectives? And most importantly, are these educational shifts genuinely enhancing the learning experience for students?

AI in Assessment: Promises and Perils

In districts where students have been historically marginalized and labeled as underachievers, Allgood's expertise, coupled with research-backed strategies, enabled personalized instruction, targeted feedback, culturally relevant content, and empathetic leadership.

Today, schools leverage numerous edtech tools to support teaching, learning, and assessment, with many now incorporating AI-powered features. Amidst competing priorities and strained resources, teachers are increasingly turning to generative AI for assistance with feedback.

This raises a critical concern: What are the implications when we delegate the assessment of student learning and the grading of their work to AI?

Data Privacy and Algorithmic Bias: A Troubling Trend

A significant portion of educational technology applications share students' personal data with third parties. There is a concerning lack of definitive data confirming the privacy of Early Warning System (EWS) data, despite research indicating its potential effectiveness when used for family and school interventions.

A stark example emerged in 2021 when a Florida school district shared EWS data that categorized students as "at-risk." This data was subsequently used by county police departments, through school resource officers, to label students as exhibiting "future delinquency" and being "destined to a life of crime."

Further compounding these concerns, a 2023 study analyzing over a million records from Wisconsin's Dropout Early Warning System over a decade found that the tool did not improve graduation rates. Instead, it relied on demographic data, including race and income, inadvertently labeling Black, Hispanic, and low-income students. Alarmingly, eight out of ten students flagged as "at-risk" were misidentified.

The human element in education, particularly in assessment, offers a depth of understanding that algorithms currently cannot replicate. It is this nuanced, empathetic, and context-aware evaluation that fosters true student growth and ensures that data serves as a tool for support, not for predetermined labels.